EOCG Model

This Mendeley Data repository "EOCG Model" contains R code to run Empirical Orthogonal Constraint Generation (EOCG), a model aimed at learning a reduced set of dimensions to solve a Multidimensional Knapsack Problem (MKP). The R code also runs the two models ORIGINAL and HYP. The code has been used in the following research article: T. Setzer and S. M. Blanc, Corrigendum to “Empirical Orthogonal Constraint Generation for Multi-Dimensional 0/1 Knapsack Problems” [European Journal of Operational Research, 282, 1 (2020), 58–70], https://doi.org/10.1016/j.ejor.2019.12.029. Corresponding author: Thomas Setzer, E-mail address: [e-mail]. (DOI of original article: https://doi.org/10.1016/j.ejor.2019.09.016). Computational results presented in the referenced manuscript are available in folder R/Results. Guidance on how to read result files is provided in R/Results/readresults.txt.本名为“EOCG模型”的Mendeley数据仓库包含用于运行经验正交约束生成（Empirical Orthogonal Constraint Generation, EOCG）的R代码，该模型旨在学习一组降维维度以求解多维背包问题（Multidimensional Knapsack Problem, MKP）。该R代码同时可运行ORIGINAL与HYP两个模型。 本代码已应用于下述学术论文： T. Setzer与S. M. Blanc，《〈多维0-1背包问题的经验正交约束生成〉勘误》[《欧洲运筹学杂志》，282卷第1期，2020年，第58-70页]，https://doi.org/10.1016/j.ejor.2019.12.029。通讯作者：Thomas Setzer，电子邮箱：[e-mail]。（原文论文的DOI：https://doi.org/10.1016/j.ejor.2019.09.016） 已发表于上述论文的计算实验结果可于R/Results文件夹中获取。 关于结果文件的读取方法，可参考R/Results/readresults.txt文档。